System and Method for Vehicle Telematics Data

ABSTRACT

A system and method are disclosed herein to receive preliminary telematics data collected by a smartphone and actual telematics data collected by a data collection device. The system includes a computer memory and a processor in communication with the computer memory. The computer memory stores the data indicative of preliminary telematics data collected by the smartphone, including at least one of geo-position information of the vehicle and vehicle kinematics data. The processor is configured to calculate an initial benefit based upon the preliminary telematics data, and apply the initial benefit in exchange for receiving the data indicative of actual telematics data via the data collection device within the vehicle. When the received data indicative of the actual telematics data meets a pre-determined condition, the processor may compute a final benefit based on the actual telematics data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of co-pending U.S. patentapplication Ser. No. 14/715,272 entitled “System And Method ForReceiving Actual Telematics Data For A Vehicle Based On Determination OfAn Initial Benefit From Preliminary Telematics Data Collected By ASmartphone” and filed on May 18, 2015, which is a continuationapplication of U.S. patent application Ser. No. 13/529,115 entitled“System and Method to Determine an Initial Insurance Policy BenefitBased on Telematics Data Collected by a Smartphone” and filed on Jun.21, 2012, issued as U.S. Pat. No. 9,037,394, which claims priority fromU.S. Provisional Application No. 61/650,040 entitled “System and MethodAssociated with Telematics Data” and filed on May 22, 2012, the entirecontents of each of which are incorporated herein by reference for allpurposes.

FIELD OF THE INVENTION

In general, the invention relates to a computerized system and methodfor determining an insurance policy benefit based on telematics data.

BACKGROUND OF THE INVENTION

The insurance industry has begun exploring the use of telematics sensorsand other location-aware devices associated with motor vehicles as a wayof determining driver behavior and, from this, driver risk for thepurposes of underwriting, pricing, renewing, and servicing vehicleinsurance. The devices can capture very high frequency information onlocation, speed, vehicle handling, vehicle characteristics, and otherfactors, which can be used in setting vehicle insurance rates. This datamay be used to identify safety events, such as a moment of relativelyhigh de-acceleration (e.g., a “hard brake” event). The data may alsoindicate if a vehicle is often driven during times of relatively highrisk (e.g., late at night) and/or at speeds above a predeterminedthreshold (e.g., above 75 miles per hour). It can be difficult, however,to encourage drivers to provide such data and/or to adjust drivinghabits in ways that may lower risk.

SUMMARY

Therefore, there is a need in the art for ways to encourage drivers toprovide telematics information and/or modify behaviors so as to reduce alikelihood of accidents and losses. Such measures may, according to someembodiments, use safety events calculated from location informationand/or other vehicle data, such as speed, orientation, and acceleration.Statistical analysis of the data may be used to classify safety eventsas being associated with different intensity levels.

Accordingly, systems and methods are disclosed herein to determine abenefit for an insurance policy. In some embodiments, a processor isconfigured to calculate and apply an initial insurance policy benefit,calculated based on preliminary telematics data collected by asmartphone, in exchange for receiving data indicative of actualtelematics data. When the data indicative of actual telematics datameets a pre-determined condition, the processor may compute a finalbenefit and replace the initial benefit with the final benefit.

In some embodiments, a processor may receive data indicative oftelematics data collected from a sensor coupled to a vehicle, whereinthe telematics data includes at least one of geo-position informationand kinematics data. The processor may identify safety events andassociated safety event locations based on the telematics data.Indications of the safety events may then be displayed to a driver on amap display.

According to another aspect, the invention relates to computerizedmethods for carrying out the functionalities described above. Accordingto another aspect, the invention relates to non-transitory computerreadable medium having stored therein instructions for causing aprocessor to carry out the functionalities described above.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an architectural model of a system for determining a discountfor an insurance premium based on telematics data, according to anillustrative embodiment of the invention.

FIG. 2 is a block diagram of a computing system as used in FIG. 1,according to an illustrative embodiment of the invention.

FIG. 3 is a block diagram of a vehicle and a device coupled to thevehicle for collecting telematics data, according to an illustrativeembodiment of the invention.

FIG. 4 illustrates an automobile in accordance with some embodiment ofthe invention.

FIG. 5 is a flowchart of a method according to an illustrativeembodiment of the invention.

FIGS. 6 through 9 illustrate map displays in accordance with someembodiments described herein.

FIGS. 10 and 11 illustrate current telematics displays according to someembodiments.

FIG. 12 illustrates a safety score display according to someembodiments.

FIG. 13 illustrates a likely discount display according to someembodiments.

FIG. 14 illustrates how an insurance premium might change over timeaccording to some embodiments.

FIGS. 15 through 17 are examples of insurance discount calculatordisplays in accordance with some embodiments described herein.

FIG. 18 is a block diagram of an insurance platform provided inaccordance with some embodiments.

FIG. 19 is a tabular portion of a telematics database in accordance withsome embodiments.

DESCRIPTION OF CERTAIN ILLUSTRATIVE EMBODIMENTS

To provide an overall understanding of the invention, certainillustrative embodiments will now be described, including systems andmethods for determining an insurance premium discount or other benefitusing geo-spatial information and/or other telematics data. However, itwill be understood by one of ordinary skill in the art that the systemsand methods described herein may be adapted and modified as isappropriate for the application being addressed and that the systems andmethods described herein may be employed in other suitable applications,and that such other additions and modifications will not depart from thescope thereof.

FIG. 1 is a block diagram of a system 100 for determining a discount foran insurance premium based on telematics data according to anillustrative embodiment. The system 100 uses data collected alongmultiple trips traveled by a vehicle, including, for example, speedinginformation, time of day information, and/or safety event information.An insurance company may use route data, such as Global PositioningSatellite (“GPS”) latitude and longitude data, acceleration/decelerationdata, speed data, and/or vehicle orientation data collected along aroute traveled by the vehicle to determine an insurance premium discountto be associated with a driver and/or a vehicle. With a sufficientamount of data, the insurance company can calculate a level of riskscore for the driver based on, for example, the driver's driving habits.The insurance company can use the score for setting or adjusting adiscount value to be applied to an insurance premium. In someimplementations, a score or discount is determined by a third party dataprocessing service. In addition, the score or discount may be set by anunderwriter, which may be a part of the insurance company or otherwiseaffiliated with or in a third party arrangement with the insurancecompany. According to any embodiments described here, a score might beused to determine a premium price, a premium adjustment, and/or anyother benefit that may be associated with an insurance policy (e.g., adecreased deductable value or increased overall coverage amount).

The system 100 includes one or more vehicles 102, each having a datacollection device 104. The vehicle 102 may be an automobile, motorcycle,truck, bus, watercraft, aircraft, or any other vehicle operated by adriver. A data collection device 104 is coupled to a vehicle 102 forcollecting data about the vehicle's location, movements, or otherinformation that can be used to determine risk scores. For vehicles withmultiple drivers, the data may be associated with the vehicle itself orwith the individual drivers. The data collection device 104 may bepositioned inside the vehicle 102, attached to the outside of thevehicle 102, or integrated into the vehicle 102. The data collectiondevice 104 is in communication with an insurance company system 108 overa communication network 150. The data collection device 104 maycommunicate with the insurance company system 108 though a wirelessnetwork such as a cellular network or using a wireless Internetconnection. In general, the data collection device 104 can be anycomputing device or plurality of computing devices in cooperation havinga data collection sensor (e.g., an antenna or an accelerometer), aprocessor, a memory, and a means for transmitting the collected data.The customer vehicle 102 or data collection device 104 may include anantenna for receiving signals from Global Navigation Satellite System(“GNSS”) satellites, numbered 1 through “n” in FIG. 1. In oneimplementation, the data collection device 104 is also configured toprocess the collected data. In some embodiments, the data processingprotects the driver's privacy by encrypting the data, removing locationinformation, producing summary information, or taking other measures toreduce the likelihood that location information, speed information, orother sensitive information are received by the insurance company orthird parties.

In some embodiments, rather than sending collected data directly to theinsurance company system 108, the data collection device 104 sendscollected data to a data processing service 106, which processes thedata to determine a risk score and/or an appropriate premium discountfor a driver that is then sent to the insurance company system 108. Thiscan help protect a driver's privacy, since the insurance company doesnot get detailed data about a driver's location, but only receivessummary information. Using a data processing service 106 is in someimplementations also preferable to having the data collection device 104process data to output a risk score because it reduces the processingpower needed by data collection device 104 and because using a thirdparty data processing service 106 may also make it more difficult fordrivers to tamper with the data. The data processing service 106 canperform additional monitoring functions, such as vehicle securitymonitoring or providing location-based alerts (e.g., alerting a parentor employer when a vehicle travels an unusual path) and/or speed alerts.Note that an insurance company might received detailed reports from thethird party data processing service 106, summary reports (with certaindetails removed), and/or supplemented information (e.g., includinginformation from one or more public databases).

The insurance company system 108 includes a plurality of applicationservers 112, a plurality of load balancing proxy servers 114, aninsurance company database 116, a processing unit 120, and companyterminal 122. These computing devices are connected by a local areanetwork 124.

The application servers 112 are responsible for interacting with thedata collection device 104 and/or the data processing service 106. Thedata exchange between the insurance company system 108 and datacollection device 104 and/or data processing service 106 can utilizepush and pull technologies where the application servers 112 of theinsurance company system 108 can act as both a server and client forpushing data to the data processing service 106 (e.g., which vehicles tomonitor, when to stop data collection, rules for monitoring servicesrequested by the customer) and for pulling data from the data processingservice 106. The application servers 112 or other servers of theinsurance company system 108 can request to receive periodic data feedsfrom the data collection device 104 and/or data processing service 106.The communication between the application servers 112 and the dataprocessing service 106 can follow various known communication protocols,such as TCP/IP. Alternatively, the application servers 112 and dataprocessing service 106 can communicate with each other wirelessly, e.g.,via cellular communication, Wi-Fi, Wi-Max, or other wirelesscommunications technologies or combination of wired or wirelesschannels. The load balancing proxy servers 114 operate to distribute theload among application servers 112.

The insurance company database 116 stores information about vehicularinsurance policies. For each insurance policy, the database 116 includesfor example and without limitation, the following data fields: policycoverage, a risk rating, policy limits, deductibles, the agentresponsible for the sale or renewal, the date of purchase, dates ofsubsequent renewals, product and price of product sold, applicableautomation services (for example, electronic billing, automaticelectronic funds transfers, centralized customer service planselections, etc.), customer information, customer payment history, orderivations thereof. Note that any of the embodiments described hereinmight be associated with existing insurance policies, newly issuedinsurance policies, and/or policies that have not yet been issued (e.g.,during a trial phase before a policy is issued). According to someembodiments, information collected during a trial period may influence adiscount or other benefit that is eventually associated with aninsurance policy.

The processing unit 120 is configured for determining the price of aninsurance premium based on a risk rating for a driver or vehicle. Theprocessing unit 120 may comprise multiple separate processors, such as arisk or safety processor, which may calculates a safety rating from rawor processed data from the data collection device 104 or data processingservice 106 over the communications network 150; and a business logicprocessor, which determines a premium price for a policyholder based on,among other things, a risk score. In some embodiments, insurance premiumprices or information for making insurance pricing determinations may begenerated by a third-party underwriter, which is separate from theinsurance company system 108. An exemplary implementation of a computingdevice for use in the processing unit 120 is discussed in greater detailin relation to FIG. 2.

The company terminals 122 provide various user interfaces to insurancecompany employees to interact with the processing system 120. Theinterfaces include, without limitation, interfaces to review telematicsdata, or risk ratings; to retrieve data related to insurance policies;to manually adjust a risk rating; and to manually adjust premiumpricing. In some instances, different users may be given differentaccess privileges. For example, marketing employees may only be able toretrieve information on insurance policies but not make any changes todata. Such interfaces may be integrated into one or more websites formanaging the insurance company system 108 presented by the applicationservers 112, or they may be integrated into thin or thick softwareclients or stand alone software. The company terminals 122 can be anycomputing devices suitable for carrying out the processes describedabove, including personal computers, laptop computers, tablet computers,smartphones, servers, and other computing devices.

The user terminal 130 provides various user interfaces to customers tointeract with the insurance company system 108 over the communicationsnetwork 150. Potential customers can use user terminals 130 to retrievepolicy and pricing information for insurance policies offered by theinsurance company. Customers can enter information pertaining to changesin their insurance policy, e.g., changes in policy coverage, addition orsubtraction of drivers, addition or subtraction of vehicles, relocation,mileage information, etc. Customers can also use the user terminal 130for a pay-as-you-go insurance policy in which customers purchaseinsurance by the trip or mile.

In some embodiments, the data collection device 104 may not becontinually connected to the insurance company system 108 via thenetwork 150. For example, the data collection device 104 may beconfigured to temporarily store data if the data collection device 104becomes disconnected from the network, like when it travels out of rangeof cellular towers. When the connection is restored, the data collectiondevice 104 can then transmit the temporarily stored data to theinsurance company system 108. The data collection device 104 mayalternatively be configured to connect to the communications network 150through a user's home Wi-Fi network. In this case, the data collectiondevice 104 stores trip data until it returns to the vicinity of theuser's home, connects to the user's wireless network, and sends thedata. In some embodiments, the data collection device 104 is notconnected to the network 150 at all, but rather, data collected istransmitted to the insurance company though other means. For example, acustomer can receive a data collection device 104 from the insurancecompany, couple the device 104 to his car for a set period of time ornumber of miles, and then either mail the device 104 with the collecteddata to the insurance company system 108 or extract and send thecollected data to the insurance company system 108 via mail, email, orthough a website.

FIG. 2 is a block diagram of a computing device 200 used for carryingout at least one of an insurance premium discount determination andbusiness logic processing described in relation to FIG. 1, according toan illustrative embodiment of the invention. The computing device 200comprises at least one network interface unit 204, an input/outputcontroller 206, system memory 208, and one or more data storage devices214. The system memory 208 includes at least one Random Access Memory(“RAM”) 210 and at least one Read-Only Memory (“ROM”) 212. All of theseelements are in communication with a Central Processing Unit (“CPU”) 202to facilitate the operation of the computing device 200. The computingdevice 200 may be configured in many different ways. For example, thecomputing device 200 may be a conventional standalone computer oralternatively, the functions of computing device 200 may be distributedacross multiple computer systems and architectures. The computing device200 may be configured to perform some or all of the insurance premiumdiscount determination and business logic processing, or these functionsmay be distributed across multiple computer systems and architectures.In the embodiment shown in FIG. 2, the computing device 200 is linked,via network 150 or local network 124, to other servers or systems housedby the insurance company system 108, such as the load balancing server114, and/or the application servers 112.

The computing device 200 may be configured in a distributedarchitecture, wherein databases and processors are housed in separateunits or locations. The computing device 200 may also be implemented asa server located either on site near the insurance company system 108,or it may be accessed remotely by the insurance company system 108. Somesuch units perform primary processing functions and contain at a minimuma general controller or a processor 202 and a system memory 208. In suchan embodiment, each of these units is attached via the network interfaceunit 204 to a communications hub or port (not shown) that serves as aprimary communication link with other servers, client or user computersand other related devices. The communications hub or port may haveminimal processing capability itself, serving primarily as acommunications router. A variety of communications protocols may be partof the system, including, but not limited to: Ethernet, SAP, SAS™, ATP,BLUETOOTH™, GSM and TCP/IP.

The CPU 202 comprises a processor, such as one or more conventionalmicroprocessors and one or more supplementary co-processors such as mathco-processors for offloading workload from the CPU 202. The CPU 202 isin communication with the network interface unit 204 and theinput/output controller 206, through which the CPU 202 communicates withother devices such as other servers, user terminals, or devices. Thenetwork interface unit 204 and/or the input/output controller 206 mayinclude multiple communication channels for simultaneous communicationwith, for example, other processors, servers or client terminals.Devices in communication with each other need not be continuallytransmitting to each other. On the contrary, such devices need onlytransmit to each other as necessary, may actually refrain fromexchanging data most of the time, and may require several steps to beperformed to establish a communication link between the devices.

The CPU 202 is also in communication with the data storage device 214.The data storage device 214 may comprise an appropriate combination ofmagnetic, optical and/or semiconductor memory, and may include, forexample, RAM, ROM, flash drive, an optical disc such as a compact discand/or a hard disk or drive. The CPU 202 and the data storage device 214each may be, for example, located entirely within a single computer orother computing device; or connected to each other by a communicationmedium, such as a USB port, serial port cable, a coaxial cable, anEthernet type cable, a telephone line, a radio frequency transceiver orother similar wireless or wired medium or combination of the foregoing.For example, the CPU 202 may be connected to the data storage device 214via the network interface unit 204.

The CPU 202 may be configured to perform one or more particularprocessing functions. For example, the computing device 200 may beconfigured for calculating a risk or safety score for a driver orvehicle. The same computing device 200 or another similar computingdevice may be configured for calculating an aggregate risk rating basedon multiple safety scores (e.g., associated with different clusters ofsimilar routes). The same computing device 200 or another similarcomputing device may be configured for calculating an insurance premiumdiscount for a vehicle or driver based at least the risk scores and/orthe safety rating.

The data storage device 214 may store, for example, (i) an operatingsystem 216 for the computing device 200; (ii) one or more applications218 (e.g., computer program code and/or a computer program product)adapted to direct the CPU 202 in accordance with the present invention,and particularly in accordance with the processes described in detailwith regard to the CPU 202; and/or (iii) database(s) 220 adapted tostore information that may be utilized to store information required bythe program. The database(s) 220 may including all or a subset of datastored in insurance company database 116, described above with respectto FIG. 1, as well as additional data, such as formulas or manualadjustments, used in establishing the insurance risk for a vehicle.

The operating system 216 and/or applications 218 may be stored, forexample, in a compressed, an uncompiled and/or an encrypted format, andmay include computer program code. The instructions of the program maybe read into a main memory of the processor from a computer-readablemedium other than the data storage device 214, such as from the ROM 212or from the RAM 210. While execution of sequences of instructions in theprogram causes the CPU 202 to perform the process steps describedherein, hard-wired circuitry may be used in place of, or in combinationwith, software instructions for implementation of the processes of thepresent invention. Thus, embodiments of the present invention are notlimited to any specific combination of hardware and software.

Suitable computer program code may be provided for scoring risk based ontelematics data associated with a plurality of trips taken by a vehicleor driver over a period of time. The program also may include programelements such as an operating system, a database management system and“device drivers” that allow the processor to interface with computerperipheral devices (e.g., a video display, a keyboard, a computer mouse,etc.) via the input/output controller 206.

The term “computer-readable medium” as used herein refers to anynon-transitory medium that provides or participates in providinginstructions to the processor of the computing device (or any otherprocessor of a device described herein) for execution. Such a medium maytake many forms, including but not limited to, nonvolatile media andvolatile media. Nonvolatile media include, for example, opticalmagnetic, or opto-magnetic disks, or integrated circuit memory, such asflash memory. Volatile media include Dynamic Random Access Memory(“DRAM”), which typically constitutes the main memory. Common forms ofcomputer-readable media include, for example, a floppy disk, a flexibledisk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM,DVD, any other optical medium, punch cards, paper tape, any otherphysical medium with patterns of holes, a RAM, a PROM, an EPROM orElectronically Erasable Programmable Read-Only Memory (“EEPROM”), aFLASH-EEPROM, any other memory chip or cartridge, or any othernon-transitory medium from which a computer can read.

Various forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to the CPU 202 (or anyother processor of a device described herein) for execution. Forexample, the instructions may initially be borne on a magnetic disk of aremote computer (not shown). The remote computer can load theinstructions into its dynamic memory and send the instructions over anEthernet connection, cable line, or even telephone line using a modem. Acommunications device local to a computing device (e.g., a server) canreceive the data on the respective communications line and place thedata on a system bus for the processor. The system bus carries the datato main memory, from which the processor retrieves and executes theinstructions. The instructions received by main memory may optionally bestored in memory either before or after execution by the processor. Inaddition, instructions may be received via a communication port aselectrical, electromagnetic or optical signals, which are exemplaryforms of wireless communications or data streams that carry varioustypes of information.

FIG. 3 is a block diagram of a vehicle 102 having a data collectiondevice 104. As described with regard to FIG. 1, the vehicle 102 may bean automobile, motorcycle, truck, bus, watercraft, aircraft, or anyother vehicle operated by a driver. The vehicle 102 includes a vehiclecomputer 302, an On-Board Diagnostics (“OBD”) port 304, and vehicletelematics sensors 306. The data collection device 104 is connected tothe vehicle 102 via an OBD port connector 322 connected to the OBD port304 to receive telematics data and other information. The datacollection device 104 includes a CPU 310, a GNSS receiver 312, anaccelerometer 314, memory 316, a user interface 318, and a wirelesscommunications device 320. The CPU 310 is in communication with theother elements of the data collection device 104 to facilitate theoperation of the data collection device 104. The CPU can also beconfigured to process data received from the GNSS receiver 312, theaccelerometer 314, and the OBD port connector 322. Data processing mayinclude calculating risk scores, calculating safety ratings, calculatingintermediate values for determining insurance premium discounts, orencrypting data sent by the wireless communications device 320.

The Global Navigation Satellite System (“GNSS”) receiver 312 includes anantenna and associated signal processing circuitry for receiving signalsfrom GNSS satellites, such as the satellites numbered 1 through n inFIG. 1, and determining its location from the signals. GNSS satellitesmay be, for example, GPS, GLONASS, Galileo, or Beidou satellites whichsend time and orbital data from which the data collection device 104 cancalculate its location. In some configurations, the CPU 310 calculatesthe location of the vehicle from data from the receiver 312. The CPU 310can pull location data from the GNSS receiver 312 at set time intervals,such as every 0.1 seconds, 0.2 seconds, 0.5 seconds, 1 second, 2seconds, 7 seconds, or 10 seconds. The CPU 310 sends the location datato the memory 316 along with a time and date stamp indicating when thevehicle was at the location. In some embodiments, the GNSS receiver 312may be part of a separate GNSS device used by the driver for obtainingdriving directions. In this case, the GNSS receiver 312 transmits datato the data collection device 104 though a wired connection or awireless connection, e.g., BLUETOOTH or Wi-Fi.

The accelerometer 314 is a device that measures proper acceleration.Data collected from an accelerometer 314 may include or be used forobtaining the g-force, acceleration, orientation, shock, vibration,jerk, velocity, speed, and/or position of the vehicle. Some or all ofthese types of data are received or calculated by the CPU 310. The CPU310 may collect data at intervals such as every 0.1 seconds, 0.2seconds, 0.5 seconds, 1 second, 2 seconds, 7 seconds, or 10 seconds andstore the data in the memory 316. Each data point is time and datestamped and/or location stamped. In some embodiments, the CPU 310determines intervals between data stored in the memory 316 based ontrends in the data. The rate of data collection may vary based onvehicle behavior; for example, if a driver is travelling along astraight road at a consistent speed, the CPU 310 may save data lessfrequently than if the driver is making frequent turns. In someembodiments, only “exception data” evident of safety events or otherunusual driving behavior is stored. For example, the CPU 310 may onlysave accelerations, decelerations, hard turns, speeds, lane changespeeds, etc. with rates above a certain threshold.

The OBD port connector 322 is used to collect data from the vehiclecomputer 302 and/or vehicle telematics sensors 306 via OBD port 304. Thevehicle computer 302 may provide information about the vehicle's speed,the number of miles traveled, whether the vehicle is running or not,seatbelt usage, airbag deployment, and vehicle diagnostics. Vehiclediagnostics data can be used to determine whether a safety event wascaused by the driver's actions or related to a vehicle malfunction, suchas low tire pressure, low oil pressure, high engine temperature, loss ofpower, and stalling. The vehicle may contain additional telematicssensors 306 for, e.g., vehicle tracking, monitoring gasolineconsumption, and vehicle safety. Data obtained by the data collectiondevice 104 from the vehicle computer 302 and telematics sensors 306 viathe OBD port 304 can supplement or be used instead of data collected bythe GNSS receiver 312 and/or accelerometer 314. In some embodiments, thedata collection device 104 turns on automatically when the vehicle isturned on; the data collection device 104 may be powered by the vehicle102.

The data collection device 104 also includes a wireless communicationsdevice 320 for sending collected data to and receiving commands from thedata processing service 106 and/or insurance company system 108 via thenetwork 150. The data collection device 104 may also be configured forcommunication with the driver or a passenger via user interface 318. Theuser interface 318 includes output components, such as a screen orspeakers, and input components, such as a touch screen, keyboard, ormicrophone. The user interface 318 can output risk data, route summarydata, vehicle diagnostics data, and any data collected from the GNSSreceiver 312, accelerometer 314, and/or OBD port 304. In someembodiments, the data collection device 104 is also a navigation devicethat can calculate and display a route to a destination inputted by theuser.

The vehicle 102 and data collection device 104 may be associated with,for example, an automobile. For example, FIG. 4 illustrates anautomobile 400 in accordance with some embodiment of the invention. Theautomobile 400 includes one or more sensors 410 that may be used tocollect telematics information, such as a GNSS receiver or similardevice. Note that telematics information might instead be associatedwith, for example, a motorcycle, a recreational vehicle, a boat, anairplane, etc.

FIG. 5 is a flowchart of a method 500 for determining an insurancepolicy benefit for a driver or vehicle based on telematics data. Themethod 500 can be performed by the data collection device 104, the dataprocessing service 106, the insurance company system 108, or anycombination of these. The method 500 includes the step of collectingpreliminary telematics data via a smartphone associated with a driver ofa vehicle (Step S510), For example, a smartphone application might timeof day information associated with driving, day of week, location,velocity, and/or mileage information.

An initial benefit is calculated based on the preliminary telematicsdata and a policy is issued in accordance with that benefit in exchangefor receiving data indicative of actual telematics data (Step S520). Forexample, an insurance company may offer a driver a 5% initial discountto his or her insurance premium if he or she agrees to participate in atelematics program. Another driver, associated with preliminarytelematics data (collected by a smartphone) indicating a potentiallyhigher level or risk might only be offered a 3% initial premiumdiscount. Other examples of policy benefits include a monetary discount(e.g., 100 dollars), an insurance coverage amount, and/or a deductableamount. If the driver agrees, the insurance company may provide thedriver with an apparatus, including sensors, storage means, and/or atransmitted, to be installed in his or her vehicle. The calculatedinitial benefit may, according to some embodiments, encourage drivers toparticipate in the telematics program.

The method 500 may further include the storage of actual telematics datareceived from a sensor “within” the vehicle (Step S530). As used herein,a sensor may be “within” a vehicle if it is attached to the vehicle(e.g., either inside or outside the body of the vehicle), is powered bythe vehicle, or is otherwise inside or associated with the vehicle. Toobtain actual telematics data (step S530), data from receivers andsensors such as GNSS receiver 312, accelerometer 314, vehicle computer302, and vehicle telematics sensors 306 may be collected by the datacollection device 104 and stored in the memory 306 of the datacollection device 306 and/or sent to the data processing service 106 orinsurance company system 108.

It may then be determined that the data indicative of the actualtelematics data meets a pre-determined condition (Step S530). Forexample, an insurance company might determine that actual telematicsdata has been collected from a driver for three consecutive months or2,000 miles. After the pre-determined condition has been met, a finalbenefit for the insurance policy may be computed based on the telematicsdata; and the initial discount may be replaced with the final discount(Step S540). For example, based on actual telematics data it may bedetermined that the driver should actually receive a 16% discount. Inthis case, the initial 5% discount would be replaced by the 16% discountfor the insurance policy. According to some embodiments, an indicationof the final benefit for the insurance policy may be output (e.g., shownon a display or included in an email message to the driver).

According to some embodiments, prior to computing the final benefit, arange of potential benefits may be computed based on at least a portionof the actual telematics data. For example, consider a program where afinal discount is not calculated until three months of telematics datahas been collected. In this case, after two months of telematics datahas been collected, a likely range of potential insurance discountsmight be predicted and output to the driver. For example, a driver mightbe told that based on his or her driving habits during those two months,a discount of between 8% and 12% should be expected.

The telematics data used to compute a final discount or other insurancepolicy benefit might include, for example, times of day associated withdriving, velocities associated with driving, distances associated withdriving, weather information, and/or traffic information. Moreover, theinsurance company might identify safety events within the telematicsdata (e.g., hard brake events) and/or a severity estimation of thesafety events. Moreover, according to some embodiments an insuranceplatform might output an indication of a suggested driving modificationalong with a discount or other benefit goal for the insurance premium ofthe automobile insurance policy. For example, the driving modificationmight include a suggested route to a destination to achieve a 15%discount for an insurance premium

According to some embodiments, information about safety events may bedisplayed to a driver on a map display. For example, referring now toFIG. 6, a diagram 650 depicting a user interface 602 is shown. The userinterface 602 may be displayed on device 600 such as a mobile telephone,PDA, personal computer, or the like. For example, the device 600 may bea PC, an IPHONE® from Apple, Inc., a BLACKBERRY® from RIM, a mobilephone using the Google ANDROID® operating system, or the like. The userinterface 602 depicts a portion of a map showing a portion of FairfieldCounty in the State of Connecticut. The user interface 602 may displaythe location of safety events 654, 656 (e.g., locations of rapidde-acceleration, speeding events, etc.) collected in connection with alldrivers who have provided telematics data while driving in that area. Inthis way, a driver may be alerted and take extra precautions whendriving in an area of relatively high risk.

In some embodiments, such as the one depicted in FIG. 6, identifiedsafety events 654, 656 may associated with a plurality of differentevent types and a substantial number of drivers. For example, safetyevents 654, 656 associated with both hard braking events and excessivespeeding may be displayed in connections with thousands of drivers. Notethat a driver may instead be more interested in his or her own personalsafety events. For example, referring now to FIG. 7, a diagram 750depicting a user interface 702 is shown. As before, the user interface702 may be displayed on device 700 such as a mobile telephone and maydepict a portion of a map. The user interface 702 may display to adriver the location of safety events 754, 756 (e.g., locations of rapidde-acceleration) that were a result of his or her driving habits. Inthis way, a driver may be become aware of unsafe driving habits andadjust his or her behaviors to reduce the risk of an accident.

Note that driving habits and conditions may change over time. Thus,according to some embodiments a driver may interact with a map displayto view safety events associated with a selected range of dates and/ortimes. For example, referring now to FIG. 8, a diagram 850 depictinganother user interface 802 is shown. As before, the user interface 802may be displayed on device 800 such as a mobile telephone and may depicta portion of a map. The user interface 802 may display to a driver thelocation of safety events 854, 856 (e.g., locations of rapidde-acceleration) that occurred during a particular period of time (e.g.,during the prior 24 hours, the prior week, the prior month, the prioryear, etc.). Note that the safety events 854, 856 might be associatedwith the driver's own driving habits or may reflect those of all driverswho have provided telematics data. According to some embodiments, adriver may interact with a “sliding scale” bar to select which period oftime should be used to filter the safety events 854, 856. Note that theidentified safety events 854, 856 may associated with a plurality ofdifferent event types. For example, safety events 854, 786 associatedwith both hard braking events and excessive speeding may be displayed.In this case, different labels (e.g., reflecting event types “1,” “2,”or “3” as illustrated in FIG. 8), icons, or colors may be used todifferentiate event types. Similarly, the safety events 854, 856 may beassociated with different levels of risk or severity (e.g., high,medium, and low intensity events) and these may also be differentiatedon the user interface 802.

In some cases, a driver might be interested in a particular type ofsafety event. According to some embodiments, a selection of a particularevent type may be received from the driver and only indications of thesafety events associated with that particular event type may bedisplayed to the driver on the map display (e.g., only hard brakeevents). For example, referring now to FIG. 9, a diagram 950 depictinganother user interface 902 is shown. As before, the user interface 902may be displayed on device 900 such as a mobile telephone and may depicta portion of a map. The user interface 902 may display to a driver thelocation of safety events 954, 956 (e.g., locations of rapidde-acceleration) that are of particular interest to the driver. In theexample of FIG. 9, the driver has selected to view all high intensitybrake events. Note that the safety events 954, 956 might be associatedwith the driver's own driving habits or may reflect those of all driverswho have provided telematics data. Moreover, selection of a particularevent icon might result in the display of further details about thatparticular event (e.g., the date and time the event occurred). Inaddition to, or instead of, filtering safety events based on event typeor severity, a driver might be able to display events associated with aparticular type of driver or vehicle (e.g., based on age, drivingexperience, gender, etc.).

In addition to the locations where safety events occurred, a drivermight be interested in his or her overall performance in connection withone or more types of safety events and/or how that performance comparesto others, how that performance is modifying his or her currentinsurance premium discount, etc. FIG. 10 illustrates a currenttelematics display 1000 according to some embodiments. In particular,the display 1000 includes a graphical representation 1010 of informationabout a particular risk variables derived from telematics data which maybe categorized as “below average,” “average,” or “above average” from arisk perspective. The display 1100 also includes a current score (e.g.,calculated at least in part based on the risk variable) and a currentdiscount (e.g., determined based on the current score). The currentdiscount might, according to some embodiments, represent the finaldiscount or other benefit described with respect to Step S540 of FIG. 5.Note that the graphical representation 1010 might instead be a slidingscale, letter grade (“B+”), or any other type of indication. In additionto, or instead of, a current number of events per week, a driver mightbe shown an average number of events for all drivers or for a particulartype of driver or vehicle (e.g., based on age, driving experience,gender, etc.).

FIG. 11 illustrates another current telematics display 1100 according tosome embodiments. In particular, the display 1100 includes a graphicalrepresentation of information about three different risk variablesderived from telematics data, a current score (e.g., calculated based onthe risk variables) and a current discount or other policy benefit(e.g., determined based on the current score). The current discountmight, according to some embodiments, represent the final discount.According to some embodiments, the current discount might be calculatedin substantially real time or be recalculated using new data when thedriver's safety scores are more likely change, e.g., if the customermoves, changes jobs, has a child, or retires, or at certain timeperiods, e.g., every year, every two years, every three years, everyfive years, every ten years, etc. In some embodiments, both prospectivepricing and retroactive pricing are used. For example, a customer beingcontinually monitored might receive a premium discount for a time periodbased on one or more past safety scores, and if the customer's actualscore rating for the time period was greater than or less than theexpected rating, an adjustment may be applied as appropriate.

By way of example only, a score model might consist of two mainelements: (1) a percentage of time speeding over a threshold value(e.g., 75 miles per hour) and (2) an annualized miles value associatedwith times of day. Each driver's score might, for example, start withfifteen (15) points then be modified by adding speeding points and/orsubtracting time of day mileage by the factors shown below:

For Time of Day:

Risk Level Per Mile Subtraction Risky 0.005 Moderate 0.0025 Low 0.00125Where “risky” is defined as driving between midnight and 4:00 am everyday of the week, “moderate” is driving from 4:00 am to 6:00 am and 9:00pm to midnight every day of the week and 6:00 am to 9:00 am and 3:00 pmto 6:00 pm on weekdays. “Low” risk times may comprise all other times ofthe day.

For Speeding Over a Threshold:

% Time Speeding Points >0.75% 0 0.1 -0.75% 5  <0.1% 10

In such an example, consider a driver who drives 5,000 annualized miles.Moreover, 4,000 of these miles are driven during moderate risk times ofthe day and 1,000 of these miles are driven during low risk times of theday. Moreover, the driver speeds over the threshold 0.05% of the time.In this case, a safety score might be determined as follows:

Safety Score=15+10−(4,000*0.0025+1,000*0.00125)=13.75

Rounding this to the nearest whole number and looking it up in arisk/discount table, the driver might receive a 14% discount for his orher insurance premium.

As another example, aggressive driving/hard braking events might beclassified into different intensity or severity levels. For example, atype 1 event might have a threshold of from 340 to 500 milli-g (˜changein speed or velocity (delta-V) of greater than +/−7.5 mph/sec²) (e.g.,from 14 mph to 25 mph in 1 second). A type 2 event might have athreshold of from 501 to 750 milli-g (˜change in speed or velocity(delta-V) of greater than +/−11 mph/sec²) (e.g., from 65 mph to 45 mphin 1 second). A type 3 event might have a threshold of 750 milli-g(˜change in speed or velocity (delta-V) of greater than +/−16.5mph/sec²) (e.g., from 65 mph to 35 mph in 1 second). The severity of theevent may then be used when determining an insurance premium discount ofthe driver.

Note that a driver's safety score will change over time based on his orher driving habits. FIG. 12 is an example of a safety score display 1200that might be provided to a driver according to some embodiments. Inparticular, the display 1200 includes a graph 1210 showing the driverssafety score over a particular period of time (e.g., over the last monthor year). According to some embodiments, a driver may select the periodof time depicted on the graph 1210. Such a safety score display 1200 mayencourage a driver to improve his or her safety score and become a lessrisky driver.

An insurance premium discount or other benefit may be based at least inpart on telematics data, a driver's safety score, and/or safety eventsthat occur over time. According to some embodiments, a final discountvalue may not be determined until telematics data has been collected fora predetermined period of time and/or a predetermined number of miles.Even before the final discount value is determined, a likely discountvalue might be calculated based on a driver's known driving habits. Forexample, during a trial or initial period, a likely discount value mightbe calculated based on safety events that have occurred during the trialperiod. FIG. 13 illustrates a likely discount display 1300 according tosome embodiments. In particular, the display 1300 includes a currentmost likely discount 1310 calculated based on the existing telematicsdata that has been collected for that driver. Moreover, an upper likelydiscount 1320 and lower likely discount 1330 may also be displayed(e.g., there might be a 90% chance that the driver's final discount willnot exceed the upper likely discount 1320). Note that as more telematicsdata is collected over time, the upper and lower likely discounts 1320,1330 might converge until, at the end of a trial period, the finalpremium discount is actually computed for the driver.

According to some embodiments, an initial insurance policy benefit mightbe calculated based on preliminary telematics data collected by asmartphone and be provided to a driver while actual telematics data iscollected. FIG. 14 is an illustration 1400 of how an insurance premiummight change over time according to some embodiments. A baselineinsurance premium associated with what a driver would pay if he or shedid not participate in a telematics program is represented by a dashedline 1410 in FIG. 14 along with a solid line 1420 representing his orher actual premiums that begin on the date the insurance policy isissued (represented by a dotted line in FIG. 14). During a period 1430prior to issuance of the insurance policy, preliminary telematics datais collected by a driver's smartphone. After the policy is issued andthe driver agrees to participate in the program, actual telematics datais collected 1440 (e.g., by devices provided by the insurance companyand installed in the vehicle) until a pre-determined condition is met(e.g., three months of actual telematics data has been collected).During this time 1440, the driver's insurance premium is reduced by aninitial discount amount that is calculated based at least in part on thepreliminary telematics data collected by the driver's smartphone duringtime 1430. After the pre-determined condition is met, a final discountamount is determined and applied to his or her insurance premium (andthe final amount might be more or less than the initial discountdepending on his or her driving habits as reflected by the actualtelematics data).

It may be difficult for a driver to predict or understand exactly howhis or her driving habits will adjust a safety score or premium discountvalue. According to some embodiments, a telematics calculator may beprovided for a driver to reduce this problem. For example, FIG. 15 is anexample of a telematics calculator 1500 display according to someembodiments. The telematics calculator 1500 includes an entry box 1510where a user can enter a predicted number of hard brake events that heor she expects will occur each week. The calculator 1500 also displayshow many hard brake events are currently occurring each week based onthe collected telematics data. Similarly, the driver may enter how manyspeeding events he or she predicts will occur. After entering thesevalues, the driver may activate a “calculate” icon 1520 causing thesystem to display a predicted score and/or premium discount value basedon the predicted hard brake and speeding events. In this way, a drivermay be encouraged to reduce these types of events and improve his or herdriving habits.

As another example, FIG. 16 is a telematics calculator 1600 where adriver can predict safety events of various severity or intensitylevels. In the example of FIG. 16, a driver predicts how many “high,”“medium,” and “low” intensity hard brake events will occur each week.According to other embodiments, a graphical representation 1610 may beused to reflect the entered information and/or may be used instead bythe driver to enter information (e.g., by rotating a gauge or dial).Based on this information, the calculator 1600 may generate and displaya predicted score and/or discount value.

According to other embodiments, a driver might enter a desired score orpremium discount value. For example, FIG. 17 is an example of aninsurance discount calculator 1700 in accordance with some embodimentsdescribed herein. The calculator 1700 may receive from a driver adesired premium discount via a sliding scale 1710 (e.g., in the exampleof FIG. 17 the driver is interested in receiving a 10% discount). Basedon the desired discount, the calculator 1700 generates a number ofsafety events for various types of events and/or various levels ofseverity. For example, the calculator 1700 might indicate that 5 highintensity hard brake events should be experienced per week in order forthe driver to receive a 10% discount. The calculator 1700 may be, forexample, associated with a web page, a smartphone application, and/or akiosk and may encourage drivers to adopt less risky driving habits.

The processes described herein may be performed by any suitable deviceor apparatus. FIG. 18 is one example of an insurance platform 1800according to some embodiments. The insurance platform 1800 may be, forexample, associated with the system 108 of FIG. 1. The insuranceplatform 1800 comprises a processor 1810, such as one or morecommercially available CPUs in the form of one-chip microprocessors,coupled to a communication device 1820 configured to communicate via acommunication network (not shown in FIG. 18). The communication device1820 may be used to communicate, for example, with one or more remotevehicles or third party services. The insurance platform 1800 furtherincludes an input device 1840 (e.g., a mouse and/or keyboard to enterinsurance discount information) and an output device 1850 (e.g., acomputer monitor to display aggregated insurance reports and/or resultsto an administrator).

The processor 1810 also communicates with a storage device 1830. Thestorage device 1830 may comprise any appropriate information storagedevice, including combinations of magnetic storage devices (e.g., a harddisk drive), optical storage devices, and/or semiconductor memorydevices. The storage device 1830 stores a program 1812 and/or scoringsystem 1814 for controlling the processor 1810. The processor 1810performs instructions of the programs 1812, 1814, and thereby operatesin accordance with any of the embodiments described herein. For example,the processor 1810 may receive telematics data associated with avehicle. The processor 1810 may also analyze the telematics data and/ortransmit discount information to a potential entity to be insured basedat least in part on a computed risk score.

Referring again to FIG. 18, the programs 1812, 1814 may be stored in acompressed, uncompiled and/or encrypted format. The programs 1812, 1814may furthermore include other program elements, such as an operatingsystem, a database management system, and/or device drivers used by theprocessor 1810 to interface with peripheral devices.

As used herein, information may be “received” by or “transmitted” to,for example: (i) the insurance platform 1800 from another device; or(ii) a software application or module within the insurance platform 1800from another software application, module, or any other source.

In some embodiments (such as shown in FIG. 18), the storage device 1830stores an underwriting database 1860 and/or a telematics database 1900.An example of a database that may be used in connection with theinsurance platform 1800 will now be described in detail with respect toFIG. 19. Note that the database described herein is only one example,and additional and/or different information may be stored therein.Moreover, various databases might be split or combined in accordancewith any of the embodiments described herein.

Referring to FIG. 19, a table is shown that represents the telematicsdatabase 1900 that may be stored at the insurance platform 1800according to some embodiments. The table may include, for example,entries identifying users, drivers, or vehicles. The table may alsodefine fields 1902, 1904, 1906, 1908, 1910 for each of the entries. Thefields 1902, 1904, 1906, 1908, 1910 may, according to some embodiments,specify: a driver identifier 1902, a policy identifier 1904, time of dayinformation 1906, speeding information 1908, and an applicable discount1910. The information in the telematics database 1900 may be created andupdated, for example, whenever data is received from remote vehicles.

The driver identifier 1902 may be, for example, a unique alphanumericcode identifying a customer or potential customer (e.g., a person orbusiness). The policy identifier 1904 might represent an insuranceproduct that may be offered to the user associated with the driveridentifier 1902. The time of day information 1906 might represent anestimated number of hours driven per year during high, moderate, and/orlow risk times of day. The speeding information 1908 might indicate apercent of time the driver spends driving above a threshold value (e.g.,75 miles per hour). The applicable discount might represent, forexample, an initial pre-determined discount value, a predicted value,and/or a final value calculated based on collected telematics data.

The following illustrates various additional embodiments of theinvention. These do not constitute a definition of all possibleembodiments, and those skilled in the art will understand that thepresent invention is applicable to many other embodiments. Further,although the following embodiments are briefly described for clarity,those skilled in the art will understand how to make any changes, ifnecessary, to the above-described apparatus and methods to accommodatethese and other embodiments and applications.

Although specific hardware and data configurations have been describedherein, not that any number of other configurations may be provided inaccordance with embodiments of the present invention (e.g., some of theinformation associated with the databases described herein may becombined or stored in external systems).

The present invention has been described in terms of several embodimentssolely for the purpose of illustration. Persons skilled in the art willrecognize from this description that the invention is not limited to theembodiments described, but may be practiced with modifications andalterations limited only by the spirit and scope of the appended claims.

What is claimed is:
 1. A vehicle telematics data management computersystem comprising: a data storage device configured to store dataindicative of preliminary telematics data collected by a first datacollection device within a vehicle and data indicative of actualtelematics data collected by a second data collection device within thevehicle; an application server configured to: receive the dataindicative of preliminary telematics data collected by the first datacollection device within the vehicle during a first time period;determine, based on the data indicative of preliminary telematics data,an initial safety-related benefit linked to driver participation in atelematics program; responsive to receipt of data indicative of driverparticipation in the telematics program; push, to a third-partytelematics data processing platform, monitoring parameters for thethird-party telematics data processing service to receive telematicsdata for the vehicle, during a second time period after the first timeperiod, from the second data collection device within the vehicle,wherein the monitoring parameters include a stop parameter for stoppingcollection of the second time period telematics data, the stop parametercorresponding to a pre-determined condition for collection of the secondtime period telematics data; receive, from the third-party telematicsdata processing platform based upon the second time period telematicsdata received by the third-party telematics data processing service andthe monitoring parameters, date indicative of the actual telematics datacollected by the second data collection device within the vehicle;determine, based on the information corresponding to the actualtelematics data, a final safety-related benefit, and output anindication of the final safety-related benefit.
 2. The computer systemof claim 1, wherein the application server is further configured todetermine the final safety-related benefit to be greater or less thanthe initial safety-related benefit depending on driving habits reflectedby the data collected during the second time period.
 3. The computersystem of claim 1, wherein the application server is further configuredto issue a policy to the driver responsive to receipt of data indicativeof driver participation in the telematics program, and the initialsafety-related benefit and the final safety-related benefits arebenefits associated with the policy.
 4. The computer system of claim 1,wherein the application server is further configured to: pull dataassociated with the telematics data collected during the second timeperiod from the third-party telematics data processing platform.
 5. Thecomputer system of claim 4, wherein the pulled data associated with thetelematics data collected during the second time period from thethird-party telematics data processing platform does not includelocation data corresponding to the vehicle.
 6. The computer system ofclaim 1, wherein the first data collection device and the second datacollection device comprise a same device.
 7. The computer system ofclaim 1, wherein the stop parameter of the monitoring parameterscorresponds to one of a time duration and a cumulative driving distance.8. The computer system of claim 1, wherein the information correspondingto the actual telematics data received by the application server fromthe third-party telematics data processing platform comprises one of arisk score and a discount value.
 9. The computer system of claim 1,wherein the first data collection device and the second data collectiondevice being within the vehicle comprises the first data collectiondevice and the second data collection device being one of: inside thevehicle, attached to an outside of the vehicle, or integrated into thevehicle.
 10. The computer system of claim 1, wherein the second datacollection device is configured to encrypt the actual telematics dataand remove one or both of location information and speed informationfrom the actual telematics data.
 11. A computer-implemented methodcomprising: receiving, by an application server of a vehicle telematicsdata processing computer system, data indicative of preliminarytelematics data collected by a first data collection device within thevehicle for a first time period; storing, in a data storage devicecoupled to the application server, the data indicative of preliminarytelematics data; determining, by the application server based on thedata indicative of preliminary telematics data, an initial vehiclesafety-related benefit to be applied at commencement of a second timeperiod, after the first time period, and associated with driverparticipation in a telematics program; responsive to receiving dataindicative of an agreement to participate in a telematics program from adriver: pushing, by the application server to a third-party telematicsdata processing service, monitoring parameters for receiving second timeperiod telematics data for the vehicle from a second data collectiondevice within the vehicle, wherein the monitoring parameters include astop parameter for stopping collection of the second time periodtelematics data, the stop parameter corresponding to a pre-determinedcondition for collection of the second time period telematics data;receiving, by the application server from the third-party telematicsdata processing platform based upon the second time period telematicsdata received by the third-party telematics data processing platform andthe monitoring parameters, information corresponding to actualtelematics data collected by the second data collection device withinthe vehicle; storing, by the data storage device, the informationcorresponding to the actual telematics data collected by the second datacollection device within the vehicle; determining, by the applicationserver based on the information corresponding to the actual telematicsdata, a final vehicle safety-related benefit, wherein the final vehiclesafety-related benefit may be greater or less than the initial vehiclesafety-related benefit depending on driving habits reflected by thetelematics data collected during the second time period; and outputting,by the application server, an indication of the final vehiclesafety-related benefit.
 12. The computer-implemented method of claim 11,wherein the final safety-related benefit is determined to be greater orless than the initial safety-related benefit depending on driving habitsreflected by the data collected during the second time period.
 13. Thecomputer-implemented method of claim 11, further comprising, responsiveto receiving data indicative of an agreement to participate in atelematics program from the driver, issuing a risk mitigation policy tothe driver, and the initial safety-related benefit and the finalsafety-related benefits are benefits associated with the policy.
 14. Thecomputer-implemented method of claim 11, further comprising pulling, bythe application server, data associated with the second time periodtelematics data from the third-party telematics data processing service.15. The computer-implemented method of claim 14, wherein the pulled dataassociated with the second time period telematics data from thethird-party telematics data processing platform does not includelocation data corresponding to the vehicle.
 16. The computer-implementedmethod of claim 11, wherein the first data collection device and thesecond data collection device comprise a same device.
 17. Thecomputer-implemented method of claim 11, wherein the informationcorresponding to the actual telematics data received by the applicationserver from the third-party telematics data processing platformcomprises one or more of a detailed report, a summary report, andsupplemental data corresponding to the vehicle.
 18. Thecomputer-implemented method of claim 11, wherein the first datacollection device and the second data collection device being within thevehicle comprises the first data collection device and the second datacollection device being one of: inside the vehicle, attached to anoutside of the vehicle, or integrated into the vehicle.
 19. Thecomputer-implemented method of claim 11, wherein the actual telematicsdata is encrypted and does not include one or both of locationinformation and speed information.
 20. The computer-implemented methodof claim 11, wherein the monitoring parameters further includesparameters to vary a rate of collection of the actual telematics databased on vehicle behavior.